Hunt Gather Trade

Hunt Gather Trade

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Hunt Gather Trade
Strategy X and the Trials of Development
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Strategy X and the Trials of Development

I mentioned a strategy I worked on in my previous post. This is ATS Strategy X. We take it from producing wild results in the backtest to a more realistic 1.6 profit factor and $24k on 1 NQ contract.

Larry Kann's avatar
Larry Kann
Feb 15, 2024
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Hunt Gather Trade
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Strategy X and the Trials of Development
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AI Generated. GPT 4.0. “Sad man struggling with a coding problem.”

I know. This is not a Twilight strategy. Surprise! Before dropping more strategies (and converting 44X), I’m going over what has kept me busy the past couple of weeks. This post will cover the issues I ran into while trying to code Strategy X into our framework and get it to function better in the backtest. This project stemmed from a conversation and a need in the ATS Research Group. I was originally unsure if I was going to be able to share this story and strategy, but I was given the go ahead by Celan Bryant, the author of Automated Trade Strategies.

This task was much more challenging to accomplish than I anticipated. The problem I faced was getting the strategy to calculate entry signals on each tick and get semi-reliable results in the backtest using the NinjaTrader (NT) Tick Replay function. Along with tick data (provided by NT), this is an excellent way to try and get a realistic simulation of the trades in the backtest environment.

After all the hardship of learning how to code for tick-level calculations, Strategy X comes out with a more realistic backtest that looks more like how it performs in the forward test. It has a net profit of $24k, a profit factor of 1.6, a Sharpe ratio of .84, a Sortino ratio of 5.3, and a max drawdown of $3k. These results are for the last year on 1 NQ contact on a 60-minute timeframe with no optimization. Let’s see how we go from crazy, unreliable results (over 1k trades daily) to these more believable results.

Disclaimer: the following post is an organized representation of my research and project notes. It doesn’t represent any type of advice, financial or otherwise. Its purpose is to be informative and educational. Backtest results are based on historical data, not real-time data. There is no guarantee that these hypothetical results will continue in the future. Day trading is extremely risky, and I do not suggest running any of these strategies live.

This post is for paid subscribers. Paid subscribers will have access to the private GitHub where all the Hunt Gather Code and strategies live. It is continuously being worked on and will expand as we explore the world of automated trade systems.

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